Individual patients have unique needs for medication and therapeutics, whether that might be for general wellness (e.g., vitamins or other supplements, or preventative drugs based on individualized risk factors from, for example, known environmental and genetic factors), for prevention or prophylactic purposes, or for the treatment of single or multiple acute and/or often complex and sometimes chronic disease pathologies.
The standard of care in medicine is to treat patients with various drugs, most often in pill/tablet form as an outpatient. This can often lead to a high “pill burden” and is sometimes termed polypharmacy. Poor compliance often follows. Poor adherence to medication and prescribed health of medical related regimens is a recognized medical problem in the U.S. and abroad. At least a third of all medication-related hospital admissions are caused by poor medication adherence, and these events alone are estimated to cost $100 billion annually in the USA. (PMID 18183470, J Gen Intern Med. 2008 February; 23(2):216-8. Medication Adherence After Myocardial Infarction: A Long Way Left To Go. Choudhry N K, Winkelmayer W C.) Many studies demonstrate that chronic illnesses like diabetes, hypertension, heart disease, or ulcerative colitis worsen when patients fail to take medications as prescribed—and this puts additional burdens not only on individuals, but the health care system. Additionally preventative regimens, such as taking of a statin to lower high cholesterol levels can lead to prevention of coronary artery disease, as well as the resulting disease morbidity and related costs.
For example, an adult patient with hypertension and a history of coronary artery disease (CAD) and a prior heart attack/myocardial infarction might commonly be prescribed “standard” doses of low dose (81 mg) aspirin, a cholesterol lowering medication, a beta-blocker, an ACE inhibitor, and a diuretic such as hydrochlorothiazide. Additional prescribed drugs might include digoxin, a multivitamin, and medication for blood glucose control to help manage co-morbidities such as type II diabetes.
Multiple medication prescriptions (or polypharmacy) have been shown to dramatically lower patient compliance. See, e.g., van Bruggen, R. “Refill adherence and polypharmacy among patients with type 2 diabetes in general practice.” Pharmacoepidemiol and Drug Safety. 18.11 (2009): 983-91. Many older patients are faced with up to a dozen or sometimes more separate prescribed medications ranging from pills to eye drops, requiring complex regimens, sorting and scheduling. Patient and family/caregiver education about the problems being treated or prevented, and understanding the prescribing clinicians instructions on the dosing, timing is also often non-optimal given the limitations of clinician and medical staff time-even when the basic prescribing information is on the pill bottle, many patients are not clear on what the mediation is for, or how to best take it or when not to take it, for example to ‘hold’ an anti-hypertensive when blood pressures are running low. These issues, and others can lead to poor adherence/compliance, mix-ups, underdosing and overdoses, and therefore clinical outcome suffers, leading to further disease progression, pathology, clinical needs, hospitalizations, increased healthcare costs, as well as increased morbidity and mortality. It has been estimated that 10% of hospital admissions are related to medication errors and problems with compliance.
Pharmacogenomics refers to the entire spectrum of genes that determine drug behavior and sensitivity, whereas pharmacogenetics is often used to define the narrower spectrum of inherited differences in drug metabolism and disposition. The benefits of pharmacogenomics are numerous. For example, prescribing clinicians, as well as pharmaceutical companies could exclude those people who are known to have a negative response to the drug, based upon clinical trials and potentially on correlation of side effects or other issues which correlate to one or more genes or gene variant (as determined by Single Nucleotide Polymorphism (SNP) analysis (which is available and common today) to sequencing (becoming lower cost and more common)). This, of course, increases the probability that the drug might be a success with a particular population. Pharmacogenetic and ever cheaper and more available genotyping will identify many new disease-related genes and provide an explosion of new targets to pursue; and pharmacogenomics profiling (with or without additional patient specific information) will lead to patient stratification, and these new targets, as well as existing targets, will be divided into subsets. It has been estimated that genotyping will identify new disease related genes that will lead to between 5,000 and 10,000 new potential targets. Because the current amount of targets is approximately 500 and is comprised of mainly four target classes, such as G-protein-coupled receptors ion channels, nuclear hormone receptors and enzymes, these new targets will add genomic and medicinal diversity. The FDA already has many approved drugs with pharmacogenomic information in their labels. See http://www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/uc083378.htm. And queriable databases have been compiled and continue to be expanded as new research is published, which contain various drugs and specific genes which affect them, for example the PharmGkb database (http://www.pharmgkb.org)
Some drugs are metabolized by several pharmacologic polymorphic genes (including, for example, the CYP (cytochrome P450) family of liver enzymes responsible for breaking down over 30 different classes of drugs), and other drugs (and/or dietary intake of various vitamins or other compounds) can inhibit or induce these same enzymatic and other genes/proteins. For example, Vitamin K intake (which may be provided from a diet including leafy green vegetables) can interact with warfarin (Coumadin), and components in grapefruit can interfere with several kinds of prescription medications. These combinations and their various effects should be considered when prescribing medications, but often are not known (genetics of patient aren't known) and/or not presented to the prescribing clinician, and the impact of various patient attributes (ranging from weight, to renal function) on various multi-drug effects not determined or calculated. This can lead to drug toxicity, and drug overdoses, and contribute to many of the drug related side effects, complications, morbidity and deaths which occur in the US and rest of world each year.
Additionally some drugs, based on a patient's individual attributes, may be relatively or absolutely not indicated based on genetics, history of allergic reactions, or other factors. For example, many patients are prescribed aspirin to decrease risk of cardiovascular events including heart attack and stroke. However, recent scientific published studies have indicated that individuals who do not carry the LPA gene do not show significant risk reduction from taking daily aspirin. A clinician, aware of such information, may therefore choose not to prescribe aspirin (which has known side effects and risk including gastritis and increased risk of gastrointestinal bleeding) for those patients who are not LPA carriers.
In addition to drug dosing, the selection of drug is often important and can be informed by many attributes, ranging from genes, to age, renal function etc. One example is selection of statin for a particular patient based on genes. SLCO1B1, for example, is a key gene that affects both the metabolism and side effect profile of many statins. Understanding of the pharmacogenomics of genes related to statins, can for example help determine and guide a clinician as to whether a patient is likely to benefit, which statin to choose from and which dose. Similarly for selection, combination and dosings of various medications to treat hypertension, and other acute and chronic diseases.
While medications have general doses, these often are not ideal, as they do not account for side-effects, and a patients individual characteristics (which can affect drug selection and dosing), which range from but are not limited to weight, body surface area (BSA), body mass index (BMI) or Quetelet Index, lean body mass, percentage of body fat, kidney/renal function, metabolism of different drugs based on the patient's genetics (i.e. for liver enzymes which metabolize many drugs), and known or predicted drug-drug interactions. Additional patient-specific attributes which may influence how a particular patient will respond to a given drug include degree of physical activity, exercise, diet (for example, amount of Vitamin-K in consumption of leafy green vegetables can dramatically effect dosing requirements for Coumadin), habits (including smoking and alcohol consumption), social network data, spending information.
Manufactured pill/tablet drugs however are usually “one size fits all” and are typically produced in a limited number of approved forms/dosages, and therefore in many cases under-dose the patient, and in others can lead to overdoses and other toxicities.
While individual drugs may be prescribed, as the ability of biomedical technology to achieve “personalized medicine” (i.e. the right drug(s), at the right dose, for the right person at the right time) based on genetics and other factors is becoming possible, however polypharmacy (multiple drugs prescribed), if integrated into combination dosing would greatly enhance ease of therapy, compliance (also termed ‘adherence’) and efficacy, and would translate to better prevention/prophylaxis, improved outcomes, decreased disease, suffering and lower healthcare costs.
Compounding (i.e. pharmaceutical compounding and compounding pharmacy) is the mixing (and in some cases reformulation) of drugs by a pharmacist, physician, or veterinarian to fit the unique needs of a patient. This may be done for medically necessary reasons, such as to change the form of the medication from a solid pill to a liquid, to avoid a non-essential ingredient that the patient is allergic to, or to obtain the exact dose needed or prescribed of one or more medications. It may also be done for voluntary reasons, such as adding favorite flavors to a medication. It is generally done manually by the pharmacist, is time consuming and expensive. In current standard use, compounding pharmacists can prepare and combine one or more medications using several unique delivery systems, such as a sublingual troche or lozenge, a lollipop, capsule, or a transdermal gel or cream that can be absorbed through the skin. For those patients who are having a hard time swallowing a capsule, a compounding pharmacist can make a liquid suspension instead.
In addition, clinical trials, and the safety, efficacy measures required to develop new drugs and combinations often requires extensive, rigorous and expensive and phased clinical trials. Assurance that trial subjects are actually taking the test drugs/placebo or other medical components is critical to accurate assessment. Better means of tracking compliance during clinical trials will lead to safer, more effective drugs entering the market.
Feedback from patient to clinician is often very limited, in terms of both the impact and benefits and the side effects of one or drugs on treating the patient (includes treatment, prophylaxis, etc). Improved feedback mechanisms could enable ‘tuning’ or changing of medications to faster, more time efficient and convenient means to achieve optimal dosing, improved outcomes, minimized side effects and improved compliance. Feedback can consist of (but not be limited to) physiologic data (i.e. vital signs (blood pressure, pulse, temperature) blood chemistries (i.e. blood glucose), subjective measures (energy, mood) etc. For example a patient may be newly diagnosed with hypertension and prescribed in an informed or empiric manner one or more medications designed to lower blood pressure. As is common in medical practice today, the patient may or may not measure blood pressure values in the home or other environment, and the resulting information as to whether the medications(s) were effective is limited or lacking, and other factors which could be influencing blood pressure (including time of day, activity, diet) are not determined. Feedback mechanisms, by which the blood pressure (BP) values can be measured (for example with mobile BP measuring system which is connected via smart phone to the web and the patient record), could enable the patient, other caregivers and clinician to have insight into the effects of their medicine and impact of other factors (i.e. sleep, salt intake). By providing means for the measures from the blood pressures to be provided back to the clinicians, or a ‘intelligent system with pre-determined algorithms, rules, or decision tree type structures to then help the patient of physician decide whether a particular medication needs to be stopped, adjusted, or added to. Such a system could save time in the iteration of drug dosing and combinations, and lead to better outcomes, adherence, and cost savings.